[VoxBo] Question about FIR analysis for event-related designs

[Lila Chrysikou]

Charan,

Thank you for your response; it was very helpful in clarifying several basic
points.

As a follow up, it would seem from your comments that not generating an FIR
set for conditions that one is not directly interested in would not create
an accurate model, which makes sense.

My understanding of your description, then, is that I should be generating
different FIR sets depending on the duration of the events in my experiment.
To make this more concrete, the TR for the entire study is 3s; the
experiment includes 4 different types of events with various durations:
condition A = 12s (4TRs), condition B=12s (4 TRs), perceptual baseline=6s (2
TRs), and null events=3s (1 TR). Is there a "right" way to generate the
appropriate numbers for each of the FIR sets? For instance, would 19-20
points  for my 12s events, 15 points for my 6s events, and 10 points for my
3s events be correct?

Also, if the above is correct, how can one set up contrasts between
conditions that do not have the same number of points (e.g., an experimental
condition with 20 points, vs. a perceptual baseline with 15 points)? Should
the results be transformed somehow or should the points match?

I'm sorry for all the additional questions, but I just want to make sure I'm
doing this right.

Thanks so much again for your help-

Best,

~Lila

On Fri, Jun 6, 2008 at 6:35 PM, Charan Ranganath <cranganath at ucdavis.edu>
wrote:

> Lila, I'm not sure I understand your question because I don't know the
> duration of your TR and what you're exactly going for. But my initial hunch
> is that this isn't the way that you want to do this. In a traditional
> analysis, you have a model specifying the onset and duration of NEURAL
> activity that is convolved with a hemodynamic response. The FIR set is
> designed to model the HEMODYNAMIC response to an event, based on the onset
> of a neural event, but without strict assumptions about the duration of
> neural activity.
>
> A typical HRF lasts 16-20s. So let's say that you have a 2s TR, an event
> that is short (~2s) could be modeled with an FIR set with 8-10 points. For a
> longer event (~8s), you'd want to use more points (say 15?).
>
> Regarding whether you can include other covariates that are not modified
> w/an FIR set, that is fine. But if the other covariates are not modeled in a
> realistic way, they might either be useless or suck up variance that they
> shouldn't.
>
> Re your last question, I believe voxbo sets up a 0 covariate to model the
> onset of the event (t=0), whereas the other covariates model subsequent TRs.
>
> Hope this helps. CR
>
> Lila Chrysikou wrote:
>
>> Hello everyone,
>>
>> I am trying to analyze data from an event-related design using an FIR
>> analysis. I am interested in examining differences between two experimental
>> conditions relative to a perceptual baseline task. My experimental
>> conditions have a duration of 4TRs, whereas my Baseline has a duration of
>> 2TRs.
>> While setting up my GLMs, a couple of questions came up:
>>
>> 1) After introducing the diagonal set as a condition of interest, I have
>> selected each experimental condition and the perceptual baseline separately
>> and subsequently modified each selection with the appropriate TR for each
>> covariate type (i.e., 4 TRs for each experimental condition, 2TRs for the
>> baseline). Is that correct?
>>
>> 2) If my model includes other covariates for which I am not interested
>> regarding the FIR, can I leave them as is?
>>
>> 3) I noticed that voxbo automatically generates an additional covariate
>> (0); what does this covariate correspond to? Should one instead enter the
>> FIR TRs as n-1 to account for this?
>>
>> I haven't been able to find much information on FIR analysis on the
>> mailing list; if anyone has additional details/advice/recommended readings
>> that wouldn't mind sharing, it would be greatly appreciated.
>>
>> Many thanks in advance,
>>
>> ~Lila
>>
>> --
>> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>> Evangelia G. Chrysikou, Ph.D.
>> Post Doctoral Research Fellow
>> Thompson-Schill Lab
>>
>> Center for Cognitive Neuroscience
>> University of Pennsylvania
>> Office address: 3810 Walnut St.,Room 307, Philadelphia, PA 19104
>> 215. 573.6726 (phone)
>> 215. 898.1982 (fax)
>> E-mail: evangelg at psych.upenn.edu <mailto:evangelg at psych.upenn.edu>
>>
>
> --
> Charan Ranganath, Ph.D.
> Associate Professor
> Center for Neuroscience and Dept. of Psychology
> University of California at Davis
> 1544 Newton Ct.
> Davis, CA 95618
>
> phone: 530-757-8750
> fax: 530-757-8640
> http://entorhinal.ucdavis.edu/~evan/index.php<http://entorhinal.ucdavis.edu/%7Eevan/index.php>
>
> [PLEASE NOTE THAT OUR NORMAL LAB URL (DynamicMemoryLab.org) IS NOT WORKING]
>
>


-- 
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Evangelia G. Chrysikou, Ph.D.
Post Doctoral Research Fellow
Thompson-Schill Lab

Center for Cognitive Neuroscience
University of Pennsylvania
Office address: 3810 Walnut St.,Room 307, Philadelphia, PA 19104
215. 573.6726 (phone)
215. 898.1982 (fax)
E-mail: evangelg at psych.upenn.edu
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